Loss Function Computation And Gradient Backpropagation

Multi-backend Keras

Unique: Implements loss functions as backend-agnostic objects in keras/src/losses/ with automatic gradient computation through the active backend's autodiff system. Loss computation and backpropagation are handled transparently during training without user code, leveraging JAX's jax.grad, PyTorch's autograd, or TensorFlow's GradientTape.

vs others: Unlike PyTorch (requires manual loss computation and backpropagation) or TensorFlow (loss functions are TensorFlow-specific), Keras provides a unified loss system across all backends with automatic gradient computation and built-in loss functions for common use cases.